The system is being upgraded and no submissions will be accepted during this time.
Keyword
Health Information ManagementElectrical and Electronic Engineering
Computer Science Applications
Biotechnology
Parkinson's Disease
Journal title
IEEE Journal of Biomedical and Health InformaticsPublication Volume
24Publication Issue
11Publication Begin page
3103Publication End page
3110
Metadata
Show full item recordAbstract
Parkinson's Disease is a disorder with diagnostic symptoms that include a change to a walking gait. The disease is problematic to diagnose. An objective method of monitoring the gait of a patient is required to ensure the effectiveness of diagnosis and treatments. We examine the suitability of Extreme Gradient Boosting (XGBoost) and Artificial Neural Network (ANN) Models compared to Symbolic Regression (SR) using genetic programming that was demonstrated to be successful in previous works on gait. The XGBoost and ANN models are found to out-perform SR, but the SR model is more human explainable.ae974a485f413a2113503eed53cd6c53
10.1109/jbhi.2019.2961808